Indoor localization and tracking using posterior state distribution of hidden markov model

One of the critical components in the wireless environment is the localization of a mobile user. In this paper, the problem of location estimation and tracking of mobile user in a fixed wireless network is addressed. A strategy is proposed based on indoor propagation model and empirical map of received signal strength distribution. The proposed system models the motion dynamics of a mobile user as a hidden markov model in which each state corresponds to geo-location then tracking the mobile user location using the posterior HMM state distribution. We present experimental results that demonstrate the ability of our tracking system to estimate the user location with a high degree of accuracy.